Who am I?


Mark James Chopping

Update! I passed the viva for the PhD!

Until 22nd October 1998 I was a PhD candidate in the Department of Geography, University of Nottingham, England (supervisors : Dr. Roy Haines-Young and Dr. Michael Steven). Prior to this I read for the M.Phil. in Remote Sensing and Geographical Information Systems at Cambridge University, having worked for three years on a Cambridge University research project investigating Environmental and Cultural Conservation in Inner Asia. At Cambridge I was sent the 'best of the year' letter and in 1996 I received the Remote Sensing Society's award for the best Masters dissertation.

I am married to Xiaohong (...don't know why she puts up with me though). I appear rather ragged below since this photograph was taken at the end of a somewhat gruelling three-week field campaign in the desert and typical steppe zones of Inner Mongolia!


Mutiny on the Starship "Radiometry" : Captain Mark 'Kirk' Chopping sets his phazer on stun.

My current research goals are outlined below.

Land surface monitoring with Remote Sensing from Space : Accounting for and Using the BRDF in Monitoring Semiarid Grasslands

Of the five sources of information available in optical remote sensing (spectral, temporal, locational, directional and wave polarity), little use has been made of the last two. This research aims to explore the impact and information potential of the directional variation in the satellite signal through estimation of the surface BRDF (bidirectional reflectance distribution function) from spaceborne sensors and the AVHRR in particular.

BRDF effects make quantitative analysis via other sources of information (multispectral, multitemporal) highly problematic. The nature and extent of the impact of the BRDF on VIS and NIR reflectance is investigated using observations over different vegetated canopies in a semiarid zone, both at ground level and from two spaceborne sensors which view at large incidence angles, the AVHRR and the ATSR-2.

Linear semiempirical kernel-driven models capable of operational use are evaluated for their ability to describe and explain the BRDF, adjust the signal for BRDF effects and obtain useful surface information. Initial results indicate that the new models provide enormous scope for improving data quality and also provide useful additional information.


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